Calculate Rarity Over Time or Space

This function calculates area-based or abundance-based rarity over a gridded map or as a time series (see 'Details' for more information).

Usage

area_rarity_map(data, ...)

area_rarity_ts(data, ...)

ab_rarity_map(data, ...)

ab_rarity_ts(data, ...)

Arguments

data

A data cube object (class 'processed_cube').

...

Arguments passed on to compute_indicator_workflow

ci_type: Type of bootstrap confidence intervals to calculate. (Default: "norm". Select "none" to avoid calculating bootstrap CIs.)
cell_size: Length of grid cell sides, in km. (Default: 10 for country, 100 for continent or world)
level: Spatial level: 'cube', 'continent', 'country', 'world', 'sovereignty', or 'geounit'. (Default: 'cube')
region: The region of interest (e.g., "Europe"). (Default: "Europe")
ne_type: The type of Natural Earth data to download: 'countries', 'map_units', 'sovereignty', or 'tiny_countries'. (Default: "countries")
ne_scale: The scale of Natural Earth data to download: 'small' - 110m, 'medium' - 50m, or 'large' - 10m. (Default: "medium")
output_crs: The CRS you want for your calculated indicator. (Leave blank to let the function choose a default based on grid reference system)
first_year: Exclude data before this year. (Uses all data in the cube by default.)
last_year: Exclude data after this year. (Uses all data in the cube by default.)
spherical_geometry: If set to FALSE, will temporarily disable spherical geometry while the function runs. Should only be used to solve specific issues. (Default is TRUE)
make_valid: Calls st_make_valid() from the sf package. Increases processing time but may help if you are getting polygon errors. (Default is FALSE).
num_bootstrap: Set the number of bootstraps to calculate for generating confidence intervals. (Default: 1000)
crs_unit_convert: Force a particular output CRS even when it has different units than the input CRS. (Default: FALSE)
shapefile_path: Path of an external shapefile to merge into the workflow. For example, if you want to calculate your indicator particular features such as protected areas or wetlands.
invert: Calculate an indicator over the inverse of the shapefile (e.g. if you have a protected areas shapefile this would calculate an indicator over all non protected areas)

Value

An S3 object with the classes 'indicator_map' or 'indicator_ts' and 'area_rarity' or 'ab_rarity' containing the calculated indicator values and metadata.

Details

Rarity

Rarity is the scarcity or infrequency of a particular species in an area. A rare species might have a small population size, a limited distribution, or a unique ecological niche (Maciel, 2021; Rabinowitz, 1981). Rarity can also be a biodiversity indicator when summed over multiple species in an area, and may provide important insight for determining conservation priorities. When measured over time, rarity may indicate potential threats or changes in the environment.

Abundance-Based Rarity

Abundance-based rarity is the inverse of the proportion of total occurrences represented by a particular species. The total summed rarity for each grid cell or year is calculated (sum the rarity values of each species present there). It is calculated as:

$$ \sum_{i=1}^{S} \frac{1}{p_i} $$

where S is the number of species and pi is the proportion of occurrences represented by species i.

Area-Based Rarity

Area-based rarity is the inverse of occupancy frequency (proportion of grid cells occupied) for a particular species. The total summed rarity for each grid cell or year is calculated (sum the rarity values of each species present there). It is calculated as:

$$ \sum_{i=1}^{S} \frac{N}{n_i} $$

where S is the number of species, N is the total number of occupied grid cells, and ni is the number of grid cells occupied by species i.

Functions

area_rarity_map():
area_rarity_ts():
ab_rarity_map():
ab_rarity_ts():

References

Maciel, E. A. (2021). An index for assessing the rare species of a community. Ecological Indicators, 124, 107424.

Rabinowitz, D. (1981). Seven forms of rarity. *Biological aspects of rare * plant conservation.

Examples

if (FALSE) { # \dontrun{
arr_map <- area_rarity_map(example_cube_1, level = "country", region = "Denmark")
plot(arr_map)
} # }
if (FALSE) { # \dontrun{
arr_ts <- area_rarity_ts(example_cube_1, first_year = 1985)
plot(arr_ts)
} # }
if (FALSE) { # \dontrun{
abr_map <- ab_rarity_map(example_cube_1, level = "country", region = "Denmark")
plot(abr_map)
} # }
if (FALSE) { # \dontrun{
abr_ts <- ab_rarity_ts(example_cube_1, first_year = 1985)
plot(abr_ts)
} # }